جست‌وجوی استاد و پژوهشگر

Simon Kingمشاهده پروفایل

استاد

• Speech Synthesis
• Speech Processing
• Acoustic Modeling
• +۴ مورد دیگر

Simon King is a Professor of Speech Processing at the University of Edinburgh , affiliated with the School of Philosophy, Psychology and Language Sciences . He serves as Director of the Centre for Speech Technology Research (CSTR) and teaches courses like Speech Processing and Speech Synthesis , while directing the MSc in Speech and Language Processing . Research Interests His research focuses on: Developing new acoustic models (e.g., Linear Dynamical Models, factorial-HMMs) for speech recognition Advancing unit selection and HMM-based speech synthesis Integrating articulatory measurement data for enhanced modeling Exploring perceptual measures in synthesis criteria Building multilingual speech systems to identify universal speech building blocks Publication Trends Simon's recent work emphasizes deep learning (DNNs, LSTMs) in speech synthesis, multilingual frameworks , and articulatory-acoustic feature integration . His studies often bridge grapheme-based modeling , perceptual error reduction , and noise-robust synthesis . Scientific Awards EPSRC Advanced Research Fellowship (2005-2009) Students & Collaborations He has supervised numerous PhD students including Rasmus Dall, Tom Merritt, and Srikanth Ronanki. Current research fellows like Mirjam Wester and Zhizheng Wu contribute to projects such as Natural Speech Technology (NST) and Simple4All .

Andrea Cavallaroمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Andrea Cavallaro is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) and Director of the Idiap Research Institute. He holds dual appointments in the School of Engineering (STI) within the Institute of Electrical Engineering and Measurements (IEM) and the School of Engineering's Education Unit (SEL-ENS). His research focuses on machine learning for multimodal perception, privacy-preserving AI, and autonomous systems. Cavallaro earned his PhD in Electrical Engineering from EPFL in 2002 and has held leadership roles including Director of Research at Queen Mary University of London and Turing Fellow at The Alan Turing Institute. Education: PhD in Electrical Engineering (EPFL, 2002) Leadership: Idiap Director, Affiliate at ELLIS Society Editorial Roles: Editor-in-Chief of Signal Processing: Image Communication (2020–2023), Senior Area Editor for IEEE Transactions on Image Processing Research Interests: Machine learning for audio-visual sensing, privacy in AI, autonomous systems perception, and ethical AI frameworks. Key projects include AlignAI (trustworthy AI alignment) and CORSMAL (multimodal object manipulation). Recent articles explore privacy-aware AI models, adversarial attacks, and multimodal perception systems. His work bridges theoretical advancements with practical applications in robotics, healthcare, and education. Awards include the Royal Academy of Engineering Teaching Prize and IAPR Fellowship. Teaching: Leads courses on deep learning ethics and multimodal AI at EPFL. Advising: Supervises 11 PhD students in areas like privacy-preserving algorithms and autonomous systems. Labs/Teams: Coordinates Idiap’s Audiovisual Intelligence and Learning Lab (LIDIAP) and collaborates on projects like GraphNEx (explainable AI via graph neural networks).

Marianne Pouplierمشاهده پروفایل

استاد

• Speech production
• Coarticulation
• Phonetic universals
• +۳ مورد دیگر

Prof. Marianne Pouplier is a Professor at the Institute of Phonetics and Speech Processing (IPS) at Ludwig Maximilian University of Munich. Her research focuses on speech production mechanisms, particularly coarticulation, phonetic universals, and language-specific variations. She investigates articulatory timing, speech errors, and cross-linguistic differences in consonant clusters using advanced methodologies like real-time MRI and electromagnetic articulography. Her work bridges theoretical models (e.g., Articulatory Phonology) with empirical data, emphasizing the interplay between phonological representation and motor execution. Key contributions include studies on nasal coarticulation, larynx dynamics, and the role of articulatory effort in speech production. Selected publications highlight her expertise in analyzing speech motor control through interdisciplinary approaches. She collaborates internationally, contributing to projects like the Bavarian Archive for Speech Signals (BAS). No awards or grants are explicitly listed, but her extensive publication record underscores her scholarly impact.

Surya Ganguliمشاهده پروفایل

دانشیار

• Theoretical Neuroscience
• Computational Neuroscience
• Machine Learning
• +۴ مورد دیگر

Surya Ganguli is an Associate Professor in the Department of Applied Physics at Stanford University, with courtesy appointments in Neurobiology and Electrical Engineering. He serves as Senior Fellow at the Stanford Institute for Human-Centered AI and is affiliated with the Stanford Neuroscience Institute , Bio-X , and Wu Tsai Neurosciences Institute . His research spans theoretical neuroscience, machine learning, and statistical mechanics. Ph.D. , UC Berkeley, Theoretical Physics (2004) M.A. , UC Berkeley, Physics (2000) M.A. , UC Berkeley, Mathematics (2004) M.Eng. , MIT, Electrical Engineering and Computer Science (1998) B.S. , MIT, Physics (1998) B.S. , MIT, Mathematics (1998) B.S. , MIT, Electrical Engineering and Computer Science (1998) His lab explores how higher-level cognitive phenomena emerge from neural network dynamics, focusing on perception, memory, attention, and decision-making . Research themes include statistical mechanics of learning , neural representational geometry , and biologically plausible learning rules . Current work examines nonlinear interactions in neural networks through the Schmidt Science Polymath Award (2023). Key article trends reveal expertise in neural coding limits (2022 Nature), synaptic plasticity models (2022 Neural Computation), and deep learning theory (2022 NeurIPS publications). His 2019 Annual Review chapter on statistical mechanics of deep learning established foundational insights into network criticality. Scientific Awards : NSF Career Award (2019) Simons Foundation Investigator (2016) McKnight Scholar Award (2015) James S. McDonnell Foundation Scholar (2014) Sloan Research Fellow (2013) As advisor, he mentors 10+ doctoral students across Applied Physics, Neurosciences, and Computer Science, including Vamshi Balanaga and Mason Kamb. His lab collaborates with experimental teams at Stanford and beyond, supported by grants from NSF , Simons Foundation , and Swartz Foundation . The Neural Dynamics & Computation Lab unites physicists, mathematicians, and neuroscientists to decode cognition through interdisciplinary methods.

Rozenn Dahyotمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +۴ مورد دیگر

Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.

Andrea Greveمشاهده پروفایل

مدرس

• Cognitive Psychology
• Memory Studies
• Neuroscience
• +۳ مورد دیگر

Dr Andrea Greve is a Lecturer in the Department of Psychology at the University of Cambridge . Her research focuses on cognitive processes related to memory, prediction error, and learning mechanisms. Key areas of interest include declarative memory formation, semantic predictions, and the influence of novelty on memory retention. She has explored topics such as word learning in variable-choice paradigms, the role of hippocampal lesions in memory binding, and predictive coding in neuroimaging contexts. Her work integrates experimental psychology with neuroscience methodologies, particularly leveraging neuroimaging techniques to investigate memory systems. Notable contributions include studies on false memory effects, the nonmonotonic relationship between object-location memory and expectedness, and the impact of prior knowledge on memory encoding. Dr. Greve has also contributed to methodological advancements, such as improved MRI anonymization for MEG coregistration. While her research spans multiple decades, recent efforts (2023–2025) emphasize predictive frameworks and their applications in understanding cognitive phenomena like semantic surprise and episodic memory formation. Her findings challenge traditional assumptions about fast mapping in adults and highlight the importance of integrating computational models with empirical data. Dr. Greve collaborates extensively with neuroimaging and cognitive science teams, contributing to interdisciplinary projects that bridge theoretical and applied research in memory systems. Her work maintains a strong focus on methodological rigor, particularly in experimental design and data interpretation.

Peter Bellمشاهده پروفایل

استاد

• Automatic Speech Recognition (ASR)
• Cross-domain and Cross-lingual Adaptation
• Speech Representation Learning
• +۴ مورد دیگر

Roles: Prof Peter Bell holds a personal chair in speech technology at the University of Edinburgh's School of Informatics and is a core member of the Centre for Speech Technology Research (CSTR). His primary research focus is automatic speech recognition (ASR), particularly in cross-domain adaptation, lightly supervised training, and minority language systems. He teaches the Automatic Speech Recognition course and advises multiple PhD students. Research Interests: Prof Bell's work spans ASR system development for diverse domains, audio-visual integration, end-to-end models, and under-resourced languages. His projects include the CoG-MHEAR healthcare initiative and the Unmute project addressing language marginalization. He has pioneered techniques for speaker adaptation, raw-waveform modeling, and multi-task learning. Commercial Activities: He advises industry on speech tech adoption, co-founded Quorate Technology (acquired by LSEG), and provides consultancy to firms developing speech solutions. His work bridges academic research with commercial impact through projects like the BBC's MGB Challenge and EU-funded SUMMA platform. Grants & Projects: Leads EPSRC-funded CoG-MHEAR and Unmute initiatives, collaborates on IARPA MATERIAL for low-resource ASR, and contributed to the SpeechWave waveform-based ASR project. His research has been supported by Bloomberg, Ericsson, Samsung, and Toshiba. Labs & Teams: Active in CSTR, leading teams in speech representation learning, adaptation techniques, and multi-modal ASR. His lab supports interdisciplinary work with NLP, HCI, and biomedical engineering groups. Personal: A passionate hillwalker, he explores Scottish Highlands and Corbetts. Previously active in Edinburgh University Hillwalking Club, his outdoor pursuits reflect his disciplined approach to research exploration.

Jiaxiang Zhangمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Cognitive Neuroscience
• +۲ مورد دیگر

Jiaxiang Zhang is Professor of Artificial Intelligence in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a PhD in Computational Neuroscience from the University of Bristol and previously held positions at the University of Birmingham, MRC Cognition and Brain Sciences Unit (Cambridge), and Cardiff University where he founded the Cognition and Computational Brain Lab. Zhang's research integrates computational modeling, machine learning, brain imaging (MEG/EEG/fMRI), and experimental approaches to study human cognition, aging, and neurological disorders. Key focus areas include: Neural mechanisms of decision-making and problem-solving Computational models of cognitive processes AI applications in healthcare diagnostics and neuroimaging Brain network dynamics in neurological conditions Recent publications emphasize deep learning models for neural data, multimodal brain connectivity, decision-making impairments in Parkinson's disease, and neuroinformatics tools. His work shows strong clinical translation through epilepsy biomarker development and emergency department outcome prediction. Zhang has led research grants from ERC, MRC, BBSRC, and Wellcome Trust. As primary investigator for multiple projects, he oversees significant computational neuroscience initiatives. He is available for postgraduate supervision.

Alexis Housenمشاهده پروفایل

استاد

• Linguistics
• Applied Linguistics
• Second Language Acquisition
• +۷ مورد دیگر

Alexis Housen is a Professor of Linguistics & Applied Linguistics at the LW Academic Unit Linguistics and Literary Studies within Vrije Universiteit Brussel . Their research focuses on second language acquisition, multilingualism, and psycholinguistics. Currently active in over 30 projects, including leadership roles in initiatives like the Eye-Catching project (2021-2024) and the International Francqui Professor program (2023-2025). Research Interests : Housen's work examines language acquisition processes, particularly in second language learning contexts. Key themes include lexis-grammar interfaces, salience effects in SLA, and the role of instruction in phonological acquisition. Their empirical studies integrate psycholinguistic methodologies with corpus-based analyses. Recent Contributions : Recent publications address salience's role in morphology acquisition, complexity metrics in L2 writing, and comparative proficiency analysis across oral/written modalities. Their work demonstrates interdisciplinary influence across linguistics, education, and cognitive science. Recognition : Awarded the European Second Language Association Fellowship (2000). Active in international collaborations, presenting at conferences like the European Second Language Association and Birkbeck College symposia. Grants & Leadership : Oversees €1.2M+ in active funding through projects like SRP-Groeifinanciering: Multilingual language control (2022-2027). Serves in leadership roles including Dean and Head of Research Groups.

Anton Bergمشاهده پروفایل

پژوهشگر ارشد

• Cognitive Science
• Computer Vision
• Religious Studies
• +۷ مورد دیگر

Anton Berg is a Postdoctoral Researcher at the University of Helsinki, affiliated with the Department of Digital Humanities within the Faculty of Arts and the Helsinki Institute for Social Sciences and Humanities (HSSH). He is also a member of the methodological unit at HSSH, focusing on interdisciplinary research at the intersection of cognitive science, religious studies, and artificial intelligence. His educational background spans computer science, cognitive science, and religious studies, enabling him to bridge technical and humanistic approaches to AI. His research primarily investigates how commercial image recognition systems interpret and categorize religious content, exploring issues of bias, representation, and the datafication of religion. Berg's research interests include computer vision systems, automatic image recognition, machine and deep learning, large language models, and the relationship between religions, worldviews, and values related to AI technologies. He particularly focuses on inequality issues, the datafication of religion, the datafication of societies, the social scientific study of religion, and the cognitive science of religion. His work combines technical analysis of AI systems with social scientific perspectives on religion and technology. His recent publications demonstrate a strong focus on examining biases in commercial image recognition services, particularly regarding religious content, with significant contributions to understanding representational silence and racial biases in these systems. He has also conducted important work on pandemic psychology, contributing to large-scale international studies on COVID-19 responses across 69 countries. Berg has been actively involved in numerous academic activities, including presentations at international conferences on topics such as computer vision in religious studies, mediatized religious populism, and biases in image recognition services. His research has been presented at venues including the International Association for the Cognitive Science of Religion. His teaching areas include religious studies, cognitive science, data science, and religion and technologies, reflecting his interdisciplinary approach to understanding the relationship between digital technologies and religious phenomena.

Silke Hamannمشاهده پروفایل

پژوهشگر

• Phonology
• Phonetics
• Language Acquisition
• +۸ مورد دیگر

Dr. Silke Hamann is a researcher at the University of Amsterdam, Faculty of Humanities, Department of Linguistics. Her work bridges phonology and phonetics, focusing on the emergence of phonological features, perceptual cues in segmental contrasts, and the interaction of phonology with orthography and language acquisition. Current projects: diachronic loanword adaptation, congenital amusia's impact on speech perception, Bantu languages (with Nancy Kula and Laura Downing), Catalan studies (with Francesc Torres-Tamarit) Research interests span synchronic/diachronic phonology, phonetic perception, computational modeling of phonological acquisition, and cross-linguistic analysis of retroflex consonants. Her publications analyze phenomena in Korean, Japanese, Bantu languages, German, Portuguese, and Slavic languages, with recurring themes of cue weighting, phonological constraints, and orthographic influence. Recent articles highlight her focus on creaky voice diagnostics, loanword phonotactics, congenital amusia, and Bantu intonation systems. Collaborations with Nancy Kula (Bantu) and Francesc Torres-Tamarit (Catalan) underscore her international research network.

Esther de Leeuwمشاهده پروفایل

دانشیار

• Multilingualism
• Bilingualism
• L1 attrition
• +۶ مورد دیگر

Esther de Leeuw is a Reader in Experimental Linguistics and Phonetics at Queen Mary University of London (QMUL), part of the School of Languages, Linguistics and Film. She holds a PhD from Queen Margaret University (Edinburgh) and completed postdoctoral research at the University of Munich and York University. Her research focuses on multilingualism, bilingualism, first language attrition, and phonetic/phonological processes. She directs QMUL's Phonetics Laboratory and co-founded Multilingual Capital, a resource for London communities. De Leeuw teaches modules on multilingualism, sociophonetics, and acoustic analysis of speech, and supervises PhD students exploring topics like bilingual pitch range and L2 perception-production links. She has held visiting fellowships in Germany and Canada, and is an Associate Editor for Second Language Research . Education: PhD in Linguistics, Queen Margaret University (2009) Magistra Artium (MA), University of Trier (Germany) Studies at University of Utrecht (Netherlands) and Northwest Community College (Canada) Research Interests: Social, cognitive, and linguistic factors in multilingual speech; phonetic/phonological attrition; bilingual executive control; sociophonetic variation. Recent work includes studies on Japanese-English bilingual pitch range, Sylheti-English prosody, and L2 perception-production disconnects. Grants & Collaborations: Led projects on phonetic attrition funded through Humboldt Fellowship and UK-based grants. Collaborates internationally with institutions including the University of Munich and the BBC Pronunciation Unit. Current research explores gender perception shifts in late bilinguals and L2 cross-modal priming effects. Labs/Initiatives: Director of QMUL Phonetics Lab, co-founder of Multilingual Capital (advocating multilingualism benefits in education).

• Auditory Cognition
• Speech Perception
• Cognitive Neuroscience
• +۵ مورد دیگر

Dr. Ediz Sohoglu is an Associate Professor in Psychology at the School of Psychology, University of Sussex. He holds a PhD in Cognitive Neuroscience from the University of Cambridge (2013) and has held academic positions at institutions including the University of Cambridge, University College London, and the MRC Institute of Hearing Research. His research focuses on auditory cognition, particularly the neural mechanisms underlying speech perception, perceptual learning, and predictive processing in auditory scenes. Education: BSc Neuroscience, University of Sussex (2003-2006) MSc Music Technology, University of York (2006-2007) PhD Cognitive Neuroscience, University of Cambridge (2009-2013) Research Interests: Dr. Sohoglu explores how expectations, attention, and prior knowledge influence auditory perception. His work combines behavioral experiments with neuroimaging techniques (EEG, MEG, fMRI) to study speech comprehension, perceptual learning of degraded sounds, and neural prediction mechanisms. Key themes include the role of prediction error in speech recognition, cortical encoding of acoustic features, and the integration of sensory input with top-down expectations. Grants & Collaborations: Predicting the future to make sense of the present: Predictive brain mechanisms for speech perception (BIAL Foundation, 2023-2024) Learning to hear again: Brain mechanisms supporting perceptual learning of degraded speech (Academy of Medical Sciences, 2022-2025) Labs & Teams: He leads the Auditory Cognition Group at Sussex, investigating auditory perception and its neural foundations. Collaborations include the MRC Cognition and Brain Sciences Unit (Cambridge) and the Ear Institute (UCL).

Pauline Larrouy-Maestriمشاهده پروفایل

پژوهشگر

• Auditory Processing
• Music Perception
• Speech Prosody
• +۵ مورد دیگر

Pauline Larrouy-Maestri is a Senior Researcher at the Max Planck Institute for Empirical Aesthetics in Frankfurt/Main, Germany, where she has been working since 2019 after serving as a Postdoctoral Researcher in the Neuroscience Department from 2014-2019. Her interdisciplinary research focuses on how humans categorize acoustic information that unfolds over time to make sense of sounds, working at the intersection of music, speech, and neuroscience. Dr. Larrouy-Maestri holds a PhD in Psychology from the University of Liège (2009-2013) and has an unusually diverse educational background including a Bachelor in Music (Piano) from the Royal Conservatory of Mons, a Master in Speech Therapy from the University of Brussels, additional studies in Psychology, Pedagogy, and Music Therapy, and research stays at McGill University and SUNY Buffalo. This multidisciplinary foundation informs her unique approach to studying sound perception. Her research examines how we process ambiguous auditory material that sits at the boundaries between music and speech categories, such as sprechgesang and West-African talking drums. She investigates auditory sequence processing in music, particularly how continuous streams of sound are parsed into meaningful units, and has made significant contributions to understanding the perception of correctness in singing. Her work on vocal communication explores how pitch, timing, and other acoustic features contribute to our interpretation of emotional content and meaning in both music and speech. Analysis of her recent publications reveals a sophisticated integration of behavioral, electrophysiological, and computational approaches to study music-speech interactions, with growing emphasis on cross-cultural perspectives, individual differences, and neural mechanisms. Her work increasingly examines how subtle acoustic variations influence aesthetic judgments and emotional responses to vocalizations. 2023: €20,000 research scholarship for "Humanity of Speech" project 2017: Selected for "Sign Up! Careerbuilding for outstanding female post docs in the MPG" 2016: Young Investigator Award from SEMPRE and ICMPC14 2015: PBEEE Merit scholarship from Fonds de recherche du Québec 2013: Patrimoine de l'Université de Liège and FNRS fundings 2011: Grant from French Community of Belgium Dr. Larrouy-Maestri currently supervises multiple researchers including Camila Bruder, Madita Hoerster, and Zofia Hobubowska. Her research is supported by competitive grants including the recent Imminent scholarship and previous funding from Belgian and Canadian sources. She maintains extensive international collaborations with researchers including David Poeppel, Melanie Wald-Fuhrmann, Marc Pell, and others across neuroscience, psychology, and musicology disciplines. Her work is conducted within the Neuroscience Department at the Max Planck Institute for Empirical Aesthetics, where she contributes to the institute's interdisciplinary mission of studying aesthetic experiences through multiple methodological approaches. She participates in research groups focusing on auditory perception, music cognition, and the neural mechanisms underlying language and music processing, helping bridge traditionally separate fields through innovative experimental designs.

Melissa Redfordمشاهده پروفایل

استاد

• Suprasegmental sound patterns
• Speech planning and production
• Child language acquisition
• +۵ مورد دیگر

Melissa Redford is a Professor in the Department of Linguistics at the University of Oregon's College of Arts and Sciences. Her research focuses on suprasegmental sound patterns, speech planning and production, and child language acquisition. She leads the Spoken Language Research Laboratories (SLRL) at the University of Oregon, where she investigates the developmental aspects of speech motor control and prosodic structure. University: University of Oregon School: College of Arts and Sciences Department: Department of Linguistics Email: redford@uoregon.edu Dr. Redford's research program aims to develop a psychologically-plausible and biologically-sensible framework for understanding spoken language production. Key areas include the acquisition of articulatory timing skills, the relationship between phrase-level representations and planning processes, and the coordination of language and breathing during speaking. Her work challenges existing theories by emphasizing the developmental structuring of linguistic representations. Analysis of her recent publications reveals ongoing focus on prosodic development, coarticulation, and speech motor control across child and adult speech. Themes include the role of cognitive load in speech production, cross-linguistic rhythm acquisition, and the integration of acoustic theories with perceptual and motor processes. She employs methods ranging from computational modeling to audiovisual speech analysis. As an advisor, Dr. Redford oversees graduate student research in the Department of Linguistics. She also contributes to the University of Oregon's academic community through her leadership of the Spoken Language Research Laboratories, which employs interdisciplinary approaches to studying speech production and perception.